Large-scale profiling and identification of potential regulatory mechanisms for allelic gene expression in colorectal cancer cells

Allelic variation in gene expression is common in humans and this variation is associated with phenotypic variation. In this study, we employed high-density single nucleotide polymorphism (SNP) chips containing 13,900 exonic SNPs to identify genes with allelic gene expression in cells from colorectal cancer cell lines. We found 2 monoallelically expressed genes (ERAP2 and MYLK4), 32 genes with an allelic imbalance in their expression, and 13 genes showing allele substitution by RNA editing. Among a total of 34 allelically expressed genes in colorectal cancer cells, 15 genes (44.1%) were associated with cis-acting eQTL, indicating that large portions of allelically expressed genes are regulated by cis-acting mechanisms of gene expression. In addition, potential regulatory variants present in the proximal promoter regions of genes showing either monoallelic expression or allelic imbalance were not tightly linked with coding SNPs, which were detected with allelic gene expression. These results suggest that multiple rare variants could be involved in the cis-acting regulatory mechanism of allelic gene expression. In the comparison with allelic gene expression data from Centre d'Etude du Polymorphisme Humain (CEPH) family B cells, 12 genes showed B-cell specific allelic imbalance and 1 noncoding SNP showed colorectal cancer cell-specific allelic imbalance. In addition, different patterns of allele substitution were observed between B cells and colorectal cancer cells. Overall, our study not only indicates that allelic gene expression is common in colorectal cancer cells, but our study also provides a better understanding of allele-specific gene expression in colorectal cancer cells.     

A Genome-Wide mQTL-seq Scan Identifies Potential Molecular Signatures Regulating Plant Height in Chickpea

The current study employed a high-throughput genome-wide next-generation sequencing-led multiple QTL-seq (mQTL-seq) strategy in two inter- and intra-specific recombinant inbred line (RIL) mapping populations to identify the major genomic regions underlying robust quantitative trait loci (QTLs) regulating plant height in chickpea. The whole genome resequencing discovered 446,475 and 150,434 high-quality homozygous single nucleotide polymorphisms (SNPs) exhibiting polymorphism between tall and dwarf/semi-dwarf mapping parents and bulk/homozygous individuals selected from each of two chickpea RIL populations. These SNP-led mQTL-seq assays in RIL mapping populations scaled-down two longer major genomic regions (1.26–1.34 Mb) underlying robust plant height QTLs into the shorter high-resolution QTL intervals (653.2–756.3 kb) on chickpea chromosomes 3 and 8. This essentially delineated regulatory novel natural SNP allelic variants from brassinosteroid insensitive 1-receptor kinase 1 (BAK1) and gibberellin (GA) 20-oxidase genes governing plant height in chickpea. A strong impact of evolutionary bottlenecks including strong artificial/natural selection on two plant height gene loci during chickpea domestication was observed. The shoot apical meristem-specific expression aside from down-regulation of two plant height genes especially in dwarf/semi-dwarf as compared to tall parents and homozygous mapping individuals of two aforementioned RIL populations was apparent. The integrated genomics-assisted breeding strategy combining mQTL-seq with differential gene expression profiling and functional allelic diversity-based trait domestication study collectively identified potential natural allelic variants of candidate genes underlying major plant height QTLs in chickpea. These functionally relevant molecular signatures can be of immense use for marker-aided genetic enhancement to develop high seed- and pod-yielding non-lodging cultivars restructured with desirable plant height in chickpea.     

Genome-wide identification of allele-specific effects on gene expression for single and multiple individuals

The analysis of allele-specific gene expression (ASE) is essential for the mapping of genetic variants that affect gene regulation, and for the identification of alleles that modify disease risk. Although RNA sequencing offers the opportunity to measure expression at allele levels, the availability of powerful statistical methods for mapping ASE in single or multiple individuals is limited. We developed a maximum likelihood model to characterize ASE in the human genome. Approximately 17% of genes displayed an allele-specific effect on gene expression in a single individual. Simulations using our model gave a better performance and improved robustness when compared with the binomial test, with different coverage levels, allelic expression fractions and random noise. In addition, our method can identify ASE in multiple individuals, with enhanced performance. This is helpful in understanding the mechanism of genetic regulation leading to expression changes, alternative splicing variants and even disease susceptibility.     

Allele-specific expression patterns reveal biases and embryo-specific parent-of-origin effects in hybrid maize

We employed allele-specific expression (ASE) analyses to document biased allelic expression in maize (Zea mays). A set of 316 quantitative ASE assays were used to profile the relative allelic expression in seedling tissue derived from five maize hybrids. The different hybrids included in this study exhibit a range of heterosis levels; however, we did not observe differences in the frequencies of allelic bias. Allelic biases in gene expression were consistently observed for approximately 50% of the genes assayed in hybrid seedlings. The relative proportion of genes that exhibit cis- or trans-acting regulatory variation was very similar among the different genotypes. The cis-acting regulatory variation was more prevalent and resulted in greater expression differences than trans-acting regulatory variation for these genes. The ASE assays were further used to compare the relative expression of the B73 and Mo17 alleles in three tissue types (seedling, immature ear, and embryo) derived from reciprocal hybrids. These comparisons provided evidence for tissue-specific cis-acting variation and for a slight maternal expression bias in approximately 20% of genes in embryo tissue. Collectively, these data provide evidence for prevalent cis-acting regulatory variation that contributes to biased allelic expression between genotypes and between tissues.     

Monozygotic twins reveal germline contribution to allelic expression differences

Variation in the level of gene expression is a major determinant of a cell's function and characteristics. Common allelic variants of genes can be expressed at different levels and thus contribute to phenotypic diversity. We have measured allelic expression differences at heterozygous loci in monozygotic twins and in unrelated individuals. We show that the extent of differential allelic expression is highly similar within monozygotic twin pairs for many loci, implying that allelic differences in gene expression are under genetic control. We also show that even subtle departures from equal allelic expression are often genetically determined.     

Validating Discovered Cis-Acting Regulatory Genetic Variants: Application of an Allele Specific Expression Approach to HapMap Populations

Background

Localising regulatory variants that control gene expression is a challenge for genome research. Several studies have recently identified non-coding polymorphisms associated with inter-individual differences in gene expression. These approaches rely on the identification of signals of association against a background of variation due to other genetic and environmental factors. A complementary approach is to use an Allele-Specific Expression (ASE) assay, which is more robust to the effects of environmental variation and trans-acting genetic factors.

Methodology/Principal Findings

Here we apply an ASE method which utilises heterozygosity within an individual to compare expression of the two alleles of a gene in a single cell. We used individuals from three HapMap population groups and analysed the allelic expression of genes with cis-regulatory regions previously identified using total gene expression studies. We were able to replicate the results in five of the six genes tested, and refined the cis- associated regions to a small number of variants. We also showed that by using multi-populations it is possible to refine the associated cis-effect DNA regions.

Conclusions/Significance

We discuss the efficacy and drawbacks of both total gene expression and ASE approaches in the discovery of cis-acting variants. We show that the ASE approach has significant advantages as it is a cleaner representation of cis-acting effects. We also discuss the implication of using different populations to map cis-acting regions and the importance of finding regulatory variants which contribute to human phenotypic variation.     

Genome-wide detection of allelic gene expression in hepatocellular carcinoma cells using a human exome SNP chip

Allelic variations in gene expression influence many biological responses and cause phenotypic variations in humans. In this study, Illumina Human Exome BeadChips containing more than 240,000 single nucleotide polymorphisms (SNPs) were used to identify changes in allelic gene expression in hepatocellular carcinoma cells following lipopolysaccharide (LPS) stimulation. We found 17 monoallelically expressed genes, 58 allelic imbalanced genes, and 7 genes showing allele substitution. In addition, we also detected 33 differentially expressed genes following LPS treatment in vitro using these human exome SNP chips. However, alterations in allelic gene expression following LPS treatment were detected in only three genes (MLXIPL, TNC, and MX2), which were observed in one cell line sample only, indicating that changes in allelic gene expression following LPS stimulation of liver cells are rare events. Among a total of 75 genes showing allelic expression in hepatocellular carcinoma cells, either monoallelic or imbalanced, 43 genes (57.33%) had expression quantitative trait loci (eQTL) data, indicating that high-density exome SNP chips are useful and reliable for studying allelic gene expression. Furthermore, most genes showing allelic expression were regulated by cis-acting mechanisms and were also significantly associated with several human diseases. Overall, our study provides a better understanding of allele-specific gene expression in hepatocellular carcinoma cells with and without LPS stimulation and potential clues for the cause of human disease due to alterations in allelic gene expression.     

Novel and functional regulatory SNPs in the promoter region of <Emphasis Type="Italic">FOXP3</Emphasis> gene in a Gabonese population

Parasites exert a selection pressure on their hosts and are accountable for driving diversity within gene families and immune gene polymorphisms in a host population. The overwhelming response of regulatory T cells during infectious challenges directs the host immune system to lose the ability to mount parasite specific T cell responses. The underlying idea of this study is that regulatory single nucleotide polymorphism (SNPs) can cause significant changes in gene expression in functional immune genes. We identified and investigated regulatory SNPs in the promoter region of the FOXP3 gene in a group of Gabonese individuals exposed to a variety of parasitic infections. We identified two novel and one promoter variants in 40 individual subjects. We further validated these promoter variants for their allelic gene expression using transient transfection assays. Two promoter variants, −794 (C/G) and the other variant −734/−540 (C/T) revealed a significant higher expression of the reporter gene at basal level in comparison to the major allele. The identification of SNPs that modify function in the promoter regions could provide a basis for studying parasite susceptibility in association studies.     

Genetics of sputum gene expression in chronic obstructive pulmonary disease

Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for gene expression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of gene expression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining gene expression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and gene expression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus.     

Allelic gene expression imbalance of bovine IGF2, LEP and CCL2 genes in liver, kidney and pituitary

Allelic expression imbalance (AEI) is an important genetic factor being the cause of differences in phenotypic traits that can be heritable. Studying AEI can be useful in searching for factors that modulate gene expression and help to understand molecular mechanisms underlying phenotypic changes. Although it was commonly recognized in many species and we know many genes show allelic expression imbalance, this phenomena was not studied on a larger scale in cattle. Using the pyrosequencing method we analyzed a set of 29 bovine genes in order to find those that have preferential allelic expression. The study was conducted in three tissues: liver, pituitary and kindey. Out of the studied group of genes 3 of them—LEP (leptin), IGF2 (insulin-like growth factor 2), CCL2 (chemokine C–C motif ligand 2) showed allelic expression imbalance.